Impact of Land Cover Changes on Reducing Greenhouse Emissions: Site Selection, Baseline Modeling, and Strategic Environmental Assessment of REDD+ Projects

Abstract

Reducing emissions from deforestation and forest degradation (REDD+) is way key to reduce the emission of greenhouse gases (GHGs) while also protecting vulnerable forest ecosystems. The purpose of this study was to recognize suitable areas for REDD+ Programme projects and calculate the reduction in CO2 emissions through the prevention of forest cover degradation in the Central Hyrcanian forests. For this purpose, the cover changes of the Central Hyrcanian forests were assessed using LANDSAT satellite images. Applying the voluntary carbon standard (VCS) methodology and the calibration period 1984–2014 (30 years), forest cover changes were predicted. The results showed that under the business‐as‐usual scenario, 155,698 ha of Central Hyrcanian forests will be declined by 2044. In general, the REDD+ Programme project implementation will prevent the release of 1,209,231 tCO2e. Based on the social cost of carbon (SCC) approach, the REDD+ Programme project implementation can save 12,092,310 US$. In addition, this approach can be used for the project design document (PDD) of the forest development mechanism.

REDD implementation for greenhouse gas reduction and climate change mitigation in Hyrcanian forests: a case study of the Kojoor Watershed, Northern Iran

“…As shown by 40 voluntary projects across nine countries, REDD projects effectively decrease deforestation and forest degradation relative to the first 5 years of their implementation (Guizar-Coutiño et al, 2022). Within the Hyrcanian forests, as evidenced by a study conducted in the Nowshahr and Noor forests (Parsamehr et al, 2023), the results of REDD baseline modeling reveal a projected release of 827,591.5 metric tons of carbon dioxide equivalent (tCO2e) over the next 30 years . However, the implementation of the REDD project in these areas is anticipated to significantly curtail this release, preventing the emission of approximately 584,056.38 tCO2e during the same period.…”

Rural Homestay Spatial Planning and Design Based on Bert BiLSTM EIC Algorithm in the Background of Digital Ecology

“…The location parameters include 10-20 kilometers from the city center, no more than five kilometers from major tourist attractions, and close to major highways or transportation hubs. Environmental factors include noise levels not exceeding 50 dB and an Air Quality Index (AQI) of less than 100 year-round.The plot parameter refers to a slightly sloping or flat, well-drained soil area within the model's applicability range of 2,000 square meters [19]. Aiming at the above hot semantic words, this study compares the spatial locations of B&B rentals near Chengdu Teachers College and Chengdu Neusoft College by combining the proposed sentiment analysis model after the relevant parameters are determined.…”